Search Results - "Data augmentation algorithm"

Component-mixing strategy: A decomposition-based data augmentation algorithm for motor imagery signals by Li, Binghua, Zhang, Zhiwen, Duan, Feng, Yang, Zhenglu, Zhao, Qibin, Sun, Zhe, Solé-Casals, Jordi

“…). However, electroencephalography (EEG) signals evoked by motor imagery (MI) are sometimes limited in their amount due to invalid data caused by the subjects…”
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A monotone data augmentation algorithm for multivariate nonnormal data: With applications to controlled imputations for longitudinal trials by Tang, Yongqiang

“… or disappears after subjects in the experimental arm discontinue the treatment. We also describe a heuristic approach to implement the controlled imputation…”
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A monotone data augmentation algorithm for longitudinal data analysis via multivariate skew-t, skew-normal or t distributions by Tang, Yongqiang

“…The mixed effects model for repeated measures has been widely used for the analysis of longitudinal clinical data collected at a number of fixed time points…”
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A monotone data augmentation algorithm for multivariate nonnormal data: with applications to controlled imputations for longitudinal trials by Tang, Yongqiang

“… or disappears after subjects in the experimental arm discontinue the treatment. We also describe a heuristic approach to implement the controlled imputation…”
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SleepContextNet: A temporal context network for automatic sleep staging based single-channel EEG by Zhao, Caihong, Li, Jinbao, Guo, Yahong

“…•Design data augmentation algorithms to improve the ability of the model to learn EEG in different sleep stages Background and objective…”
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Subject wise data augmentation based on balancing factor for quaternary emotion recognition through hybrid deep learning model by Singh, Khushboo, Ahirwal, Mitul Kumar, Pandey, Manish

“…An electroencephalogram (EEG) identifies neuronal activity as electrical currents produced by a group of specialized pyramidal cells within the brain due to…”
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Effects of Data Augmentation Method Borderline-SMOTE on Emotion Recognition of EEG Signals Based on Convolutional Neural Network by Chen, Yu, Chang, Rui, Guo, Jifeng

“… from electroencephalogram signals, and the design of classifiers with excellent performance, pose a great challenge to the subject…”
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The LZIP: A Bayesian Latent Factor Model for Correlated Zero-Inflated Counts by Neelon, Brian, Chung, Dongjun

“…) model for the analysis of correlated zero-inflated counts. The responses are modeled as independent zero-inflated Poisson distributions conditional on a set of subject-specific latent factors…”
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GAN-based sensor data augmentation: Application for counting moving people and detecting directions using PIR sensors by Yun, Jaeseok, Kim, Daehee, Kim, Dong Min, Song, Taewon, Woo, Jiyoung

“…) and generative adversarial networks (GANs). PIR output signals were collected from four multiple-subject scenarios…”
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Data augmentation for thermal infrared object detection with cascade pyramid generative adversarial network by Dai, Xuerui, Yuan, Xue, Wei, Xueye

“… (such as image flipping, random color jittering) only produce limited training samples. In order to generate images with high resolution, and ensure they are subject to the distribution of real samples, generative adversarial network (GAN) is introduced…”
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A Decoding Model of Upper Limb Movement Intention Based on Data Augmentation by Ke, Xi, Bi, Luzheng, Fei, Weijie, Feleke, Aberham Genetu

“… We used the deep convolutional generative adversarial networks(DCGANs), which is a data augmentation algorithm to generate more data to expand the training set to improve the accuracy of the model…”
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Bayesian Ensemble Tree Models for Nonparametric Problems by Li, Yinpu

“…Bayesian additive regression trees(BART) provides flexible approach to fitting a variety of regression models while avoiding strong parametric assumptions. The…”
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A bayesian approach to dynamic tobit models by Wei, Steven X.

“…) data, so that the Gibbs sampler with the data augmentation algorithm is successfully applied…”
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Supplementing the intent-to-treat analysis: Accounting for treatment failures in clinical trials by Shaffer, Michele Lee

“…Consider a two-armed, placebo-controlled trial in which subjects may experience treatment failure…”
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Bayesian causal survival analysis in clinical trials with noncompliance by Li, Fang

“…; the so-called Intent-to-treat (ITT) analysis ignores compliance information. However, noncompliance in human subjects is relatively common in clinical trials…”
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Incomplete data in event history analysis by Sutton, Christopher Julian

“… A number of methods exist for handling incomplete data. These include multiple imputation for variables subject to incompleteness and the application…”
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Representation Debiasing of Generated Data Involving Domain Experts by Bhattacharya, Aditya, Stumpf, Simone, Verbert, Katrien

“…Biases in Artificial Intelligence (AI) or Machine Learning (ML) systems due to skewed datasets problematise the application of prediction models in practice…”
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Novel Data Augmentation Employing Multivariate Gaussian Distribution for Neural Network-Based Blood Pressure Estimation by Song, Kwangsub, Park, Tae-Jun, Chang, Joon-Hyuk

“…) with standard deviation and Pearson correlation using 110 subjects contributed to the database (DB…”
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Bayesian Inference for Categorical Data with Misclassification Errors by KURODA, MASAHIRO, GENG, ZHI

“…In epidemiological studies, observed data are often collected subject to misclassification errors…”
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Optimal Artificial Neural Network for the Diagnosis of Chagas Disease Using Approximate Entropy and Data Augmentation by Rodriguez, Maria Fernanda, Cornejo, Diego Rodrigo, Diaz, Luz Alexandra, Ravelo-Garcia, Antonio, Alvarez, Esteban, Cabrera-Caso, Victor, Condori-Merma, Dante, Cornejo, Miguel Vizcardo

“… This study used a database of 292 subjects distributed into three groups: healthy volunteers (Control group…”
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